Control Engineering Practice, ISSN 0967-0661, 11/2018, Volume 80, pp. 17 - 25

Both linear and nonlinear relationships may exist among process variables, and monitoring a process with such complex relationships among variables is...

Nonlinear process monitoring | Fault detection | Randomized algorithm | Genetic algorithm | Parallel PCA–KPCA | DIAGNOSIS | PRINCIPAL COMPONENT ANALYSIS | Parallel PCA-KPCA | ALGORITHM | FAULT-DETECTION | AUTOMATION & CONTROL SYSTEMS | ENGINEERING, ELECTRICAL & ELECTRONIC | Case studies | Analysis | Algorithms

Nonlinear process monitoring | Fault detection | Randomized algorithm | Genetic algorithm | Parallel PCA–KPCA | DIAGNOSIS | PRINCIPAL COMPONENT ANALYSIS | Parallel PCA-KPCA | ALGORITHM | FAULT-DETECTION | AUTOMATION & CONTROL SYSTEMS | ENGINEERING, ELECTRICAL & ELECTRONIC | Case studies | Analysis | Algorithms

Journal Article

Mathematical Programming, ISSN 0025-5610, 6/2015, Volume 151, Issue 1, pp. 3 - 34

Coordinate descent algorithms solve optimization problems by successively performing approximate minimization along coordinate directions or coordinate...

Parallel numerical computing | 49M20 | Mathematical Methods in Physics | Calculus of Variations and Optimal Control; Optimization | Mathematics of Computing | 90C25 | Numerical Analysis | Theoretical, Mathematical and Computational Physics | Randomized algorithms | Mathematics | Combinatorics | Coordinate descent | REGRESSION | COMPUTER SCIENCE, SOFTWARE ENGINEERING | MATHEMATICS, APPLIED | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | MINIMIZATION | SHRINKAGE | CONVERGENCE | OPTIMIZATION | Analysis | Algorithms | Machine learning | Studies | Optimization algorithms

Parallel numerical computing | 49M20 | Mathematical Methods in Physics | Calculus of Variations and Optimal Control; Optimization | Mathematics of Computing | 90C25 | Numerical Analysis | Theoretical, Mathematical and Computational Physics | Randomized algorithms | Mathematics | Combinatorics | Coordinate descent | REGRESSION | COMPUTER SCIENCE, SOFTWARE ENGINEERING | MATHEMATICS, APPLIED | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | MINIMIZATION | SHRINKAGE | CONVERGENCE | OPTIMIZATION | Analysis | Algorithms | Machine learning | Studies | Optimization algorithms

Journal Article

Proceedings of the IEEE, ISSN 0018-9219, 01/2016, Volume 104, Issue 1, pp. 58 - 92

In this era of large-scale data, distributed systems built on top of clusters of commodity hardware provide cheap and reliable storage and scalable processing...

Algorithm design and analysis | Machine learning algorithms | Approximation methods | Matrix decomposition | preconditioning | randomized linear algebra | least absolute deviation | subspace embedding | Distributed databases | least squares | distributed matrix algorithms | Approximation algorithms | Big data | REGRESSION | SET | APPROXIMATION | LAPLACIAN TORTOISE | ENGINEERING, ELECTRICAL & ELECTRONIC | COMPLEXITY | ERROR | COMMUNICATION | Data processing | Algorithms | Design engineering | Construction | Computation | Design factors | Mathematical models | Computer networks | Floating point arithmetic

Algorithm design and analysis | Machine learning algorithms | Approximation methods | Matrix decomposition | preconditioning | randomized linear algebra | least absolute deviation | subspace embedding | Distributed databases | least squares | distributed matrix algorithms | Approximation algorithms | Big data | REGRESSION | SET | APPROXIMATION | LAPLACIAN TORTOISE | ENGINEERING, ELECTRICAL & ELECTRONIC | COMPLEXITY | ERROR | COMMUNICATION | Data processing | Algorithms | Design engineering | Construction | Computation | Design factors | Mathematical models | Computer networks | Floating point arithmetic

Journal Article

ACM Computing Surveys (CSUR), ISSN 0360-0300, 02/2013, Volume 45, Issue 2, pp. 1 - 40

A local algorithm is a distributed algorithm that runs in constant time, independently of the size of the network. Being highly scalable and fault tolerant,...

Local algorithms | INDEPENDENT SET | Theory | RANDOMIZED PARALLEL ALGORITHM | AD HOC NETWORKS | UNIT DISK GRAPHS | VERTEX COVER | SPANNERS | DOMINATING SET | Algorithms | APPROXIMATION ALGORITHMS | CONSTRUCTION | COMPUTER SCIENCE, THEORY & METHODS | 2-APPROXIMATION ALGORITHM | Research | Distributions, Theory of (Functional analysis)

Local algorithms | INDEPENDENT SET | Theory | RANDOMIZED PARALLEL ALGORITHM | AD HOC NETWORKS | UNIT DISK GRAPHS | VERTEX COVER | SPANNERS | DOMINATING SET | Algorithms | APPROXIMATION ALGORITHMS | CONSTRUCTION | COMPUTER SCIENCE, THEORY & METHODS | 2-APPROXIMATION ALGORITHM | Research | Distributions, Theory of (Functional analysis)

Journal Article

Journal of Heuristics, ISSN 1381-1231, 8/2016, Volume 22, Issue 4, pp. 613 - 648

This paper presents a detailed analysis of the scalability and parallelization of Local Search algorithms for constraint-based and SAT (Boolean satisfiability)...

Calculus of Variations and Optimal Control; Optimization | Constraint solving | Artificial Intelligence (incl. Robotics) | Parallel processing | Mathematics | Operations Research, Management Science | Operation Research/Decision Theory | Performance model | Randomized constraint solving | CONFIGURATION | SAT | TIME | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | DISTRIBUTIONS | SPEEDUP | COMPUTER SCIENCE, THEORY & METHODS | LOCAL SEARCH ALGORITHMS | SPECIAL-ISSUE | Models | Algorithms | Multiprocessing | Analysis | Studies | Estimating techniques | Combinatorics | Mathematical analysis | Distributed, Parallel, and Cluster Computing | Artificial Intelligence | Computer Science

Calculus of Variations and Optimal Control; Optimization | Constraint solving | Artificial Intelligence (incl. Robotics) | Parallel processing | Mathematics | Operations Research, Management Science | Operation Research/Decision Theory | Performance model | Randomized constraint solving | CONFIGURATION | SAT | TIME | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | DISTRIBUTIONS | SPEEDUP | COMPUTER SCIENCE, THEORY & METHODS | LOCAL SEARCH ALGORITHMS | SPECIAL-ISSUE | Models | Algorithms | Multiprocessing | Analysis | Studies | Estimating techniques | Combinatorics | Mathematical analysis | Distributed, Parallel, and Cluster Computing | Artificial Intelligence | Computer Science

Journal Article

Algorithmica, ISSN 0178-4617, 6/2015, Volume 72, Issue 2, pp. 607 - 619

We present a new approach to the minimum-cost integral flow problem for small values of the flow. It reduces the problem to the tests of simple multivariate...

Maximum integral flow | Theory of Computation | Parallel algorithms | Computer Systems Organization and Communication Networks | Data Structures, Cryptology and Information Theory | Processor complexity | Algorithms | Mathematics of Computing | Computer Science | Randomized algorithms | Minimum-cost flow | Polynomial verification | Algorithm Analysis and Problem Complexity | Time complexity | COMPUTER SCIENCE, SOFTWARE ENGINEERING | MATHEMATICS, APPLIED | Processor complexity | Computer science | complexity | Processor | Computational Mathematics | Mathematics | Naturvetenskap | Computer and Information Science | Datavetenskap (datalogi) | Natural Sciences | Beräkningsmatematik | Matematik | Data- och informationsvetenskap (Datateknik)

Maximum integral flow | Theory of Computation | Parallel algorithms | Computer Systems Organization and Communication Networks | Data Structures, Cryptology and Information Theory | Processor complexity | Algorithms | Mathematics of Computing | Computer Science | Randomized algorithms | Minimum-cost flow | Polynomial verification | Algorithm Analysis and Problem Complexity | Time complexity | COMPUTER SCIENCE, SOFTWARE ENGINEERING | MATHEMATICS, APPLIED | Processor complexity | Computer science | complexity | Processor | Computational Mathematics | Mathematics | Naturvetenskap | Computer and Information Science | Datavetenskap (datalogi) | Natural Sciences | Beräkningsmatematik | Matematik | Data- och informationsvetenskap (Datateknik)

Journal Article

SIAM Review, ISSN 0036-1445, 6/2011, Volume 53, Issue 2, pp. 217 - 288

Low-rank matrix approximations, such as the truncated singular value decomposition and the rank-revealing QR decomposition, play a central role in data...

Dimensionality reduction | Error rates | Approximation | Algorithms | Linear algebra | Error bounds | Eigenvalues | SURVEY and REVIEW | Matrices | Mathematical vectors | Factorization | Matrix approximation | Dimension reduction | Parallel algorithm | Pass-efficient algorithm | Random matrix | Eigenvalue decomposition | Johnson-Lindenstrauss lemma | Randomized algorithm | Interpolative decomposition | Principal component analysis | random matrix | MATHEMATICS, APPLIED | rank-revealing QR factorization | parallel algorithm | matrix approximation | randomized algorithm | streaming algorithm | dimension reduction | interpolative decomposition | eigenvalue decomposition | pass-efficient algorithm | principal component analysis | singular value decomposition | Usage | Spectral decomposition (Mathematics) | Analysis | Principal components analysis | Matrix decomposition | Error analysis (Mathematics) | Methods | Studies | Randomized algorithms | Matrix | Approximations

Dimensionality reduction | Error rates | Approximation | Algorithms | Linear algebra | Error bounds | Eigenvalues | SURVEY and REVIEW | Matrices | Mathematical vectors | Factorization | Matrix approximation | Dimension reduction | Parallel algorithm | Pass-efficient algorithm | Random matrix | Eigenvalue decomposition | Johnson-Lindenstrauss lemma | Randomized algorithm | Interpolative decomposition | Principal component analysis | random matrix | MATHEMATICS, APPLIED | rank-revealing QR factorization | parallel algorithm | matrix approximation | randomized algorithm | streaming algorithm | dimension reduction | interpolative decomposition | eigenvalue decomposition | pass-efficient algorithm | principal component analysis | singular value decomposition | Usage | Spectral decomposition (Mathematics) | Analysis | Principal components analysis | Matrix decomposition | Error analysis (Mathematics) | Methods | Studies | Randomized algorithms | Matrix | Approximations

Journal Article

Proceedings of the 50th Annual ACM SIGACT Symposium on theory of computing, ISSN 0737-8017, 06/2018, pp. 457 - 470

One of the simplest problems on directed graphs is that of identifying the set of vertices reachable from a designated source vertex. This problem can be...

shortcuts | Parallel algorithm | graph search | randomized algorithm | reachability | Shortcuts | Randomized algorithm | Graph search | Reachability

shortcuts | Parallel algorithm | graph search | randomized algorithm | reachability | Shortcuts | Randomized algorithm | Graph search | Reachability

Conference Proceeding

SIAM Journal on Optimization, ISSN 1052-6234, 2015, Volume 25, Issue 4, pp. 1997 - 2023

We propose a new randomized coordinate descent method for minimizing the sum of convex functions each of which depends on a small number of coordinates only....

Partial separability | Randomized coordinate descent | Convex optimization | Proximal methods | Parallel methods | Big data | Acceleration | Complexity | acceleration | complexity | MATHEMATICS, APPLIED | OPTIMIZATION PROBLEMS | parallel methods | MINIMIZATION | ALGORITHM | randomized coordinate descent | proximal methods | convex optimization | big data | partial separability | Mathematics | Optimization and Control

Partial separability | Randomized coordinate descent | Convex optimization | Proximal methods | Parallel methods | Big data | Acceleration | Complexity | acceleration | complexity | MATHEMATICS, APPLIED | OPTIMIZATION PROBLEMS | parallel methods | MINIMIZATION | ALGORITHM | randomized coordinate descent | proximal methods | convex optimization | big data | partial separability | Mathematics | Optimization and Control

Journal Article

Journal of the ACM (JACM), ISSN 0004-5411, 06/2019, Volume 66, Issue 3, pp. 1 - 28

Coordinating the actions of agents (e.g., volunteers analyzing radio signals in SETI@home) yields efficient search algorithms. However, such an efficiency is...

treasure hunt | Bayesian search | fault tolerance | parallel computing | randomized algorithms | distributed computing | COMPUTER SCIENCE, SOFTWARE ENGINEERING | COMPUTER SCIENCE, HARDWARE & ARCHITECTURE | COMPUTER SCIENCE, INFORMATION SYSTEMS | COMPUTER SCIENCE, THEORY & METHODS | Integers | Radio signals | Algorithms | Crashes | Search algorithms | Run time (computers) | Coordination compounds | Bayesian analysis | Boxes | Distributed, Parallel, and Cluster Computing | Computer Science

treasure hunt | Bayesian search | fault tolerance | parallel computing | randomized algorithms | distributed computing | COMPUTER SCIENCE, SOFTWARE ENGINEERING | COMPUTER SCIENCE, HARDWARE & ARCHITECTURE | COMPUTER SCIENCE, INFORMATION SYSTEMS | COMPUTER SCIENCE, THEORY & METHODS | Integers | Radio signals | Algorithms | Crashes | Search algorithms | Run time (computers) | Coordination compounds | Bayesian analysis | Boxes | Distributed, Parallel, and Cluster Computing | Computer Science

Journal Article

Theoretical Computer Science, ISSN 0304-3975, 07/2012, Volume 444, pp. 87 - 99

We deal with the well studied allocation problem of assigning n balls to n bins so that the maximum number of balls assigned to the same bin is minimized. We...

Balls and bins | Static randomized parallel load balancing algorithms | COMPUTER SCIENCE, THEORY & METHODS | Analysis | Algorithms

Balls and bins | Static randomized parallel load balancing algorithms | COMPUTER SCIENCE, THEORY & METHODS | Analysis | Algorithms

Journal Article

Australian & New Zealand Journal of Statistics, ISSN 1369-1473, 06/2019, Volume 61, Issue 2, pp. 134 - 151

Summary To study the relationship between a sensitive binary response variable and a set of non‐sensitive covariates, this paper develops a hidden logistic...

Newton–Raphson algorithm | hidden logit model | quadratic lower bound algorithm | odds ratio | non‐randomized parallel model | QUESTIONS | Newton-Raphson algorithm | STATISTICS & PROBABILITY | non-randomized parallel model | RANDOMIZED-RESPONSE | Surveys | Models | Algorithms | Regression analysis | Lower bounds | Randomization | Parameter estimation | Computer simulation | Maximum likelihood estimates | Response data analysis

Newton–Raphson algorithm | hidden logit model | quadratic lower bound algorithm | odds ratio | non‐randomized parallel model | QUESTIONS | Newton-Raphson algorithm | STATISTICS & PROBABILITY | non-randomized parallel model | RANDOMIZED-RESPONSE | Surveys | Models | Algorithms | Regression analysis | Lower bounds | Randomization | Parameter estimation | Computer simulation | Maximum likelihood estimates | Response data analysis

Journal Article

Theoretical Computer Science, ISSN 0304-3975, 12/2018, Volume 751, pp. 24 - 45

Implicit graph algorithms deal with the characteristic function χ of the edge set E of a graph G=(V,E). Encoding the nodes by binary vectors, χ can be...

Matching | Ordered Binary Decision Diagram | Almost k-wise independence | Randomized implicit algorithm | k-wise independence | Minimum spanning tree | SPACE COMPLEXITY | SET | SIZE | PARALLEL ALGORITHM | LOWER BOUNDS | TREE | CONSTRUCTIONS | COMPUTER SCIENCE, THEORY & METHODS | Algorithms

Matching | Ordered Binary Decision Diagram | Almost k-wise independence | Randomized implicit algorithm | k-wise independence | Minimum spanning tree | SPACE COMPLEXITY | SET | SIZE | PARALLEL ALGORITHM | LOWER BOUNDS | TREE | CONSTRUCTIONS | COMPUTER SCIENCE, THEORY & METHODS | Algorithms

Journal Article

SIAM Journal on Scientific Computing, ISSN 1064-8275, 2014, Volume 36, Issue 2, pp. C95 - C118

We describe a parallel iterative least squares solver named LSRN that is based on random normal projection. LSRN computes the min-length solution to min(x is...

Ridge regression | Random matrix | Random sampling | LAPACK | Rankdeficient | Iterative method | Underdetermined system | LSQR | Overdetermined system | Minimum-length solution | Randomized algorithm | Tikhonov regularization | Parallel computing | Chebyshev semi-iterative method | Sparse matrix | Linear least squares | Random projection | Preconditioning | random matrix | MATHEMATICS, APPLIED | underdetermined system | FAST RANDOMIZED ALGORITHM | ridge regression | random sampling | randomized algorithm | iterative method | preconditioning | overdetermined system | sparse matrix | rank-deficient | linear least squares | parallel computing | random projection | minimum-length solution | Least squares method | Clusters | Chebyshev approximation | Solvers | Projection | Mathematical models | Iterative methods | Linear operators | over determined system

Ridge regression | Random matrix | Random sampling | LAPACK | Rankdeficient | Iterative method | Underdetermined system | LSQR | Overdetermined system | Minimum-length solution | Randomized algorithm | Tikhonov regularization | Parallel computing | Chebyshev semi-iterative method | Sparse matrix | Linear least squares | Random projection | Preconditioning | random matrix | MATHEMATICS, APPLIED | underdetermined system | FAST RANDOMIZED ALGORITHM | ridge regression | random sampling | randomized algorithm | iterative method | preconditioning | overdetermined system | sparse matrix | rank-deficient | linear least squares | parallel computing | random projection | minimum-length solution | Least squares method | Clusters | Chebyshev approximation | Solvers | Projection | Mathematical models | Iterative methods | Linear operators | over determined system

Journal Article

The Journal of Bone and Joint Surgery, ISSN 0021-9355, 10/2018, Volume 100, Issue 19, pp. 1682 - 1690

BACKGROUND:The purpose of this study was to estimate the incidence of reoperation and the effect of implant position on the risk of reoperation within 12...

SURGERY | INTERNAL-FIXATION | ARTHROPLASTY | ALGORITHM | INTRACAPSULAR HIP-FRACTURES | BIPOLAR HEMIARTHROPLASTY | RADIOGRAPHIC ANALYSIS | RANDOMIZED CONTROLLED-TRIAL | ORTHOPEDICS | ELDERLY-PATIENTS | CANNULATED SCREWS

SURGERY | INTERNAL-FIXATION | ARTHROPLASTY | ALGORITHM | INTRACAPSULAR HIP-FRACTURES | BIPOLAR HEMIARTHROPLASTY | RADIOGRAPHIC ANALYSIS | RANDOMIZED CONTROLLED-TRIAL | ORTHOPEDICS | ELDERLY-PATIENTS | CANNULATED SCREWS

Journal Article

Journal of Parallel and Distributed Computing, ISSN 0743-7315, 2011, Volume 71, Issue 11, pp. 1427 - 1433

In this paper, 1 1 A preliminary version of this paper has been presented in HiPC 2008 Kundeti and Rajasekaran (2008) [8]. we present efficient algorithms for...

Parallel disk model | Algorithms | Randomized algorithms | External memory | Massive data sets | Sorting | Disk sorting | COMPUTER SCIENCE, THEORY & METHODS | Analysis | Models | Asymptotic properties | Mathematical analysis | Product data management | Disks | Constants | Optimization

Parallel disk model | Algorithms | Randomized algorithms | External memory | Massive data sets | Sorting | Disk sorting | COMPUTER SCIENCE, THEORY & METHODS | Analysis | Models | Asymptotic properties | Mathematical analysis | Product data management | Disks | Constants | Optimization

Journal Article

Algorithmica, ISSN 0178-4617, 5/2018, Volume 80, Issue 5, pp. 1658 - 1709

The $$(1+(\lambda ,\lambda ))$$ (1+(λ,λ)) genetic algorithm proposed in Doerr et al. (Theor Comput Sci 567:87–104, 2015) is one of the few examples for which...

Computer Systems Organization and Communication Networks | Data Structures, Cryptology and Information Theory | Algorithms | Runtime analysis | Mathematics of Computing | Computer Science | Parameter choice | Theory of Computation | Theory of randomized search heuristics | Parameter control | Algorithm Analysis and Problem Complexity | Genetic algorithms | COMPUTER SCIENCE, SOFTWARE ENGINEERING | MATHEMATICS, APPLIED | Genetic research | Analysis | Neural and Evolutionary Computing | Data Structures and Algorithms

Computer Systems Organization and Communication Networks | Data Structures, Cryptology and Information Theory | Algorithms | Runtime analysis | Mathematics of Computing | Computer Science | Parameter choice | Theory of Computation | Theory of randomized search heuristics | Parameter control | Algorithm Analysis and Problem Complexity | Genetic algorithms | COMPUTER SCIENCE, SOFTWARE ENGINEERING | MATHEMATICS, APPLIED | Genetic research | Analysis | Neural and Evolutionary Computing | Data Structures and Algorithms

Journal Article

Information Processing Letters, ISSN 0020-0190, 12/2012, Volume 112, Issue 24, pp. 976 - 979

It is shown how one can improve the reliability bound of the parallel sorting algorithm of Rajasekaran and Sen (1992) [7] that sorts uniformly distributed...

Integer sorting | Randomized algorithms | Uniformly distributed integers | Analysis of algorithms | Parallel algorithms | COMPUTER SCIENCE, INFORMATION SYSTEMS | Analysis | Algorithms | Integers | Probability theory | Keys | Data processing | Random access | Probabilistic methods | Processors | Sorting algorithms

Integer sorting | Randomized algorithms | Uniformly distributed integers | Analysis of algorithms | Parallel algorithms | COMPUTER SCIENCE, INFORMATION SYSTEMS | Analysis | Algorithms | Integers | Probability theory | Keys | Data processing | Random access | Probabilistic methods | Processors | Sorting algorithms

Journal Article

SIAM Journal on Scientific Computing, ISSN 1064-8275, 2016, Volume 38, Issue 5, pp. S508 - S538

We design efficient and distributed-memory parallel randomized direct solvers for large structured dense linear systems, including a fully matrix-free version...

Distributed memory | Tree structure | Randomized compression | Scalable algorithm | Matrix-free direct solver | HSS matrix | MATHEMATICS, APPLIED | FACTORIZATION | matrix-free direct solver | APPROXIMATION | tree structure | scalable algorithm | randomized compression | DECOMPOSITION | EQUATIONS | FAST ALGORITHMS | distributed memory | SEMISEPARABLE REPRESENTATIONS | SUPERFAST

Distributed memory | Tree structure | Randomized compression | Scalable algorithm | Matrix-free direct solver | HSS matrix | MATHEMATICS, APPLIED | FACTORIZATION | matrix-free direct solver | APPROXIMATION | tree structure | scalable algorithm | randomized compression | DECOMPOSITION | EQUATIONS | FAST ALGORITHMS | distributed memory | SEMISEPARABLE REPRESENTATIONS | SUPERFAST

Journal Article

Information Processing Letters, ISSN 0020-0190, 03/2012, Volume 112, Issue 7, pp. 277 - 281

In this note we introduce a new randomized algorithm for counting triangles in graphs. We show that under mild conditions, the estimate of our algorithm is...

Concentration of measure

Concentration of measure